Interaction with Machine Learning – Guided Project

26 January 2021


Interaction with Machine Learning – A Guided Project


8 weekly lectures sessions of 2 hours, with 3 1.5hour specialist workshops and final discussion

Application forms should be returned to CDH Learning ( by Tuesday 5 January 2021. Applications will be reviewed on a rolling basis and applicants will be notified at the latest by the end of Monday 11 January.

This Guided Project is open to graduate students and staff at the University of Cambridge. Outside the Department of Computer Science and Technology priority will be given to applicants from humanities, arts and social sciences disciplines. Early career researchers are particularly encouraged to apply. 


Lecture series: Professor Alan Blackwell (Computer Science and Technology), Advait Sarkar (Microsoft Research)

Specialist workshops: Tomasz Hollanek (Media and Technology researcher, Cambridge University) and Dr Anne Alexander (Director of Learning, Cambridge Digital Humanities)

This CDH Guided Project aims to provide humanities, arts and social science researchers with an overview of current theory and practice in the design of human-computer interaction in the age of AI and equip the participants with analytical tools necessary for a critical investigation of contemporary design with AI/ML. Looking closely at interactions between humans and emerging AI systems, the workshop will also explore the potential for interaction between humanities scholars and computer scientists in the process of development and assessment of new solutions. 

Lectures and practical research design sessions in Interaction with Machine Learning taught by Professor Alan Blackwell and Advait Sarkar (Microsoft Research) as part of an optional course for Part III and MPhil Computer Science students will form the anchoring element of the Project. These will allow researchers without a Computer Science background to explore how key challenges in AI design are being addressed within the field of interaction design, as well as identify areas in which humanities methodologies and approaches could be adopted to improve the production process, by making it more fair, critical, and socially-aware. 

Participants will also take part in three workshops specifically tailored to humanities and social science researchers and will be supported in developing a mini research project investigating how humans interact with systems based on computational models. The projects may include: 

  • probing an already existing dataset, system, or user interface from a critical perspective
  • developing an idea for new interaction design based on critical applications of ML/AI.   

Please note: no prior practical experience or knowledge of programming is required to take part in the Project, however some awareness of how AI systems work will be beneficial.


Minimum time commitment: 
  • 8 weekly online lectures led by Professor Alan Blackwell (Computer Science and Technology) and Advait Sarkar (Microsoft Research). Weekly from 26 January, 2-4pm (with the last hour as an optional session for Guided Project participants). 
  • 3 x 1.5 hour specialist workshops for humanities and social science participants led by Tomasz Hollanek and Anne Alexander (CDH) 
  • 1.5 hour project showcase and final discussion 

Participants are encouraged to set aside additional time to work on their projects between sessions. A Moodle email forum and drop-in ‘clinic’ style support sessions will be available during the Guided Project. 


Lecture topics and dates 
  • Current research themes in intelligent user interfaces (26 January, 2pm)
  • Program synthesis (2 February, 2pm) 
  • Mixed initiative interaction (9 February, 2pm)
  • Interpretability / explainable AI (16 February, 2pm) 
  • Labelling as a fundamental problem (23 February, 2pm)
  • Machine learning risks and bias (2 March, 2pm)
  • Visualisation and visual analytics (9 March, 2pm) 
  • Research presentations by Computer Science Students (16 March, 2pm) 
Workshop themes
  • AI critique, humanities methodologies and user interface design  (1 February, 10-11.30am)
  • Recommender systems (1 March 10-11.30am)
  • Machine vision (8 March 10-11.30am)
  • Project presentations and discussion (15 March 10-11.30am)



By the end of the course participants should:

  • be familiar with current state of the art in intelligent interactive systems
  • understand the human factors that are most critical in the design of such systems
  • be able to evaluate evidence for and against the utility of novel systems
  • be able to apply critical methodologies to current interaction design practices
  • understand the interplay between ML/AI research and humanities approaches